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Customer Success · Version 1.0.0 · Reviewed 2026-08-02

Customer Onboarding Stall Diagnoser

Improve milestone slippage analysis and dependency and owner detection with evidence, explicit trade-offs, and a verification plan.

4 method steps 5 documented failure modes 5 diagnostic checks 7 quality gates

Analyzes onboarding plans, milestone dates, meeting notes, and product usage to identify the exact blocked dependency, owner gap, or expectation mismatch delaying time to value.

₹149 one-time

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What this skill helps you do

  • Milestone slippage analysis
  • Dependency and owner detection
  • Recovery-plan design

How Customer Onboarding Stall Diagnoser works

You provide

Financial data, prior periods, and stated assumptions

It inspects

Volume, rate, mix, and timing behind milestone slippage analysis

It decides

A dependency and owner detection view presented as a range

You verify

Bottom-up and top-down builds reconciled, gap explained

What it checks first

Customer Onboarding Stall Diagnoser analyzes onboarding plans, milestone dates, meeting notes, and product usage to identify the exact blocked dependency, owner gap, or expectation mismatch delaying time to value. Use it when the work involves Milestone slippage analysis, Dependency and owner detection, Recovery-plan design.

  1. Whether a variance is driven by volume, rate, mix, or timing, because each implies a different response.
  2. Which assumptions carry the most sensitivity, since a forecast is only as good as its two or three dominant drivers.
  3. Whether the number is an accrual or a cash figure, which changes the conclusion entirely.
  4. One-time versus recurring components inside a trend.
  5. Whether the comparison baseline is like-for-like across periods and entity changes.

Failure modes it recognizes

  • A forecast that compounds a growth rate without a capacity or market constraint, producing an impossible outturn.
  • Mix shift making a blended margin look stable while both underlying segments deteriorate.
  • Timing differences presented as performance changes, reversing in the following period.
  • Double counting between a bottom-up and a top-down build.
  • Currency translation effects reported as operational performance.

Answers it will reject

  • Presenting a single-point forecast without a range, which conceals the uncertainty being decided on.
  • Explaining variance by restating the number rather than attributing it to a driver.
  • Changing the definition of a metric between periods without disclosure.
  • Building precision into a model whose inputs are estimates, implying false confidence.

Decision rules it applies

  • Decompose every variance into volume, rate, mix, and timing before explaining it.
  • Show a range with the assumptions that produce each bound.
  • Label each assumption as observed, derived, or estimated, and name its owner.
  • Reconcile bottom-up and top-down builds and explain the gap rather than averaging it.

Evidence it asks for

  • Build a bridge from prior period to current with each driver quantified and summing to the total.
  • Run sensitivity on the top three assumptions and report the resulting range.
  • State the review trigger: which observation would invalidate the forecast.

The method inside

  1. Reconstruct the customer journey and promised outcomes
  2. Separate activity volume from outcome and risk signals
  3. Identify the blocked dependency and accountable owner
  4. Create a jointly verifiable recovery or expansion plan

Deliverables

  • Milestone slippage analysis account brief
  • Dependency and owner detection risk and dependency map
  • Recovery-plan design action plan

Evidence requirements

  • Success plan, adoption data, support history, and meeting notes
  • Renewal date, stakeholders, expected outcomes, and risks
  • Verified customer commitments and unresolved dependencies

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Diagnose why this enterprise onboarding has been stuck for three weeks and propose a recovery plan.

Expected output

Technical configuration is complete; progress is blocked by an unowned data-approval decision. The recovery plan names the buyer decision owner, narrows the first launch scope, and resets success criteria...

Boundaries and compatibility

Ideal for

  • Milestone slippage analysis: produce a decision or artifact grounded in supplied evidence.
  • Dependency and owner detection: produce a decision or artifact grounded in supplied evidence.
  • Recovery-plan design: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Inferring customer sentiment without evidence
  • Hiding unresolved product or service failures

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.